Water Hammer Mitigation Using Hydro-Pneumatic Tanks: A Multi-Criteria Evaluation of Simulation Tools and Machine Learning Modelling

The water hammer phenomenon represents a significant challenge to the safe and efficient operation of pressurised water systems. This study investigates the application of hydro-pneumatic tanks (HPTs) as protective devices against transient flow events, with a particular focus on their integration into simplified modelling frameworks. Rigid and elastic water column models are examined, and their performance is evaluated through a representative case study. A multi-criteria decision matrix was employed to select a suitable simulation tool, leading to the adoption of the ALLIEVI software for implementing both modelling approaches. Comparative results indicate that the rigid water column model offers a favourable compromise between accuracy and computational efficiency under appropriate conditions. This supports its practical application in installing HPTs in design and operational scenarios. To further assess the predictive capacity of each model, a confusion matrix analysis was conducted across 57 scenarios. This approach proved effective in evaluating the models’ ability to anticipate pipeline rupture based on the initial configuration of the hydraulic installation. The elastic model achieved accuracy levels ranging from 90.7% to 100%, whereas the rigid water column model exhibited a slightly broader accuracy range, from 76.7% to 97.7%. These findings suggest that integrating machine learning techniques could enhance the rapid assessment of failure risks in water utility networks. Such tools may enable operators to determine in advance whether a given operating condition will likely lead to system failure, thus improving resilience and decision-making in managing pressurised pipeline systems.